CN111366989A - Weather forecasting method and device, computer equipment and storage medium - Google Patents
Weather forecasting method and device, computer equipment and storage medium Download PDFInfo
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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Abstract
The application discloses a weather forecasting method, a weather forecasting device, computer equipment and a storage medium, and relates to the technical field of weather monitoring. The weather forecast method comprises the following steps: acquiring target environment wind data of a target area in a target time period, wherein the target time period comprises a first time period and a second time period which are adjacent in time sequence, the target environment wind data comprises environment wind data of the first time period and environment wind data of the second time period, the environment wind data of the first time period is obtained according to radar echo data measured by a Doppler weather radar at the starting moment of the first time period, and the environment wind data of the second time period is obtained through calculation of a numerical weather forecast model; calculating the relative wind storm helicity according to the target environment wind data, wherein the relative wind storm helicity is used for indicating the atmospheric motion intensity; and determining the weather condition of the target area in the target time period according to the relative spiral degree of the storm. The embodiment of the application improves the accuracy of forecasting the strong convection weather.
Description
Technical Field
The present application relates to the field of weather monitoring technologies, and in particular, to a weather forecasting method, apparatus, computer device, and storage medium.
Background
The weather forecast refers to the prediction of the state of the earth atmosphere at a certain place in the future by using modern scientific technology. The weather forecast can help people to know the future weather conditions in advance, so that production and life can be adjusted in advance according to the future weather conditions to avoid unnecessary loss.
In nature, the earth's atmosphere may have various different meteorological phenomena, wherein, strong convection weather is a special meteorological phenomenon, and the strong convection weather refers to a disastrous weather with phenomena of short-term strong precipitation, thunderstorm strong wind, tornado, hail, squall lines and the like. Strong convection weather often causes economic loss and even casualties. Since the duration of the strong convection weather is generally short and has obvious burstiness, it is necessary to provide a weather forecasting method capable of accurately forecasting the strong convection weather.
Disclosure of Invention
Based on the method, the device, the computer equipment and the storage medium for weather forecast are provided.
A method of weather forecasting, the method comprising:
acquiring target environment wind data of a target area in a target time period, wherein the target time period comprises a first time period and a second time period which are adjacent in time sequence, the target environment wind data comprises environment wind data of the first time period and environment wind data of the second time period, the environment wind data of the first time period is obtained according to radar echo data measured by a Doppler weather radar at the starting moment of the first time period, the environment wind data of the second time period is obtained through calculation of a numerical weather forecast model, and the environment wind data comprises radial wind speed and latitudinal wind speed;
calculating the relative wind storm helicity according to the target environment wind data, wherein the relative wind storm helicity is used for indicating the atmospheric motion intensity;
and determining the weather condition of the target area in the target time period according to the relative spiral degree of the storm.
In one embodiment of the present application, acquiring target ambient wind data of a target area within a target time period includes:
in a plurality of first unit time periods in the first time period, obtaining environment wind data corresponding to each first unit time period through radar echo data measured by a Doppler weather radar at the starting moment of the first time period to obtain a plurality of environment wind data in the first time period;
and in a plurality of second unit time periods in the second time period, calculating and obtaining environmental wind data corresponding to each second unit time period through a numerical weather forecast model to obtain a plurality of environmental wind data in the second time period, wherein the time length of the first unit time period is the same as that of the second unit time period.
In one embodiment of the present application, calculating storm relative helicity from target ambient wind data comprises:
for each ambient wind data in the first time period and the second time period, a storm relative helicity is calculated from the ambient wind data.
In one embodiment of the present application, calculating storm relative helicity from ambient wind data comprises:
calculating storm movement speed according to the environmental wind data, wherein the storm movement speed comprises radial storm movement speed and latitudinal storm movement speed;
and calculating the relative wind storm spirality according to the environmental wind data and the wind storm moving speed.
In one embodiment of the present application, the ambient wind data includes ambient wind data for each of a plurality of levels of the atmosphere of the target area, and the calculating of the storm movement speed from the ambient wind data includes:
for each layer, calculating the storm moving speed of the layer according to the environmental wind data of the layer;
correspondingly, the storm relative helicity is calculated according to the environmental wind data, and the method comprises the following steps:
calculating the relative helicity of the storm of each layer according to the environmental wind data of each layer and the storm moving speed of each layer;
and calculating the relative spiral degree of the storm according to the relative spiral degree of the storm of each layer.
In one embodiment of the present application, there are a plurality of storm relative helicities, the method further comprising:
and generating a storm change curve according to the relative helicity of each storm, wherein the storm change curve is used for indicating the storm change trend of the target area in the target time period.
In one embodiment of the present application, determining the weather condition of the target area in the target time period according to the relative helicity of the storm comprises:
acquiring a plurality of storm relative helicity intervals, wherein different storm relative helicity intervals correspond to different weather conditions;
determining the weather condition corresponding to the relative wind storm helicity according to the relative wind storm helicity interval in which the relative wind storm helicity is located;
and determining the weather condition of the target area in the target time period according to the weather condition corresponding to the relative helicity of the storm.
A weather forecasting apparatus, the apparatus comprising:
the system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring target environment wind data of a target area in a target time period, the target time period comprises a first time period and a second time period which are adjacent in time sequence, the target environment wind data comprises environment wind data of the first time period and environment wind data of the second time period, the environment wind data of the first time period is obtained according to radar echo data measured by a Doppler weather radar at the starting moment of the first time period, the environment wind data of the second time period is obtained through calculation of a numerical weather forecast model, and the environment wind data comprises radial wind speed and latitudinal wind speed;
the calculating module is used for calculating the relative wind storm spirality according to the target environment wind data, and the relative wind storm spirality is used for indicating the atmospheric motion intensity;
and the determining module is used for determining the weather condition of the target area in the target time period according to the relative helicity of the storm.
A computer device comprising a memory and a processor, the memory storing a computer program that when executed by the processor performs the steps of:
acquiring target environment wind data of a target area in a target time period, wherein the target time period comprises a first time period and a second time period which are adjacent in time sequence, the target environment wind data comprises environment wind data of the first time period and environment wind data of the second time period, the environment wind data of the first time period is obtained according to radar echo data measured by a Doppler weather radar at the starting moment of the first time period, the environment wind data of the second time period is obtained through calculation of a numerical weather forecast model, and the environment wind data comprises radial wind speed and latitudinal wind speed;
calculating the relative wind storm helicity according to the target environment wind data, wherein the relative wind storm helicity is used for indicating the atmospheric motion intensity;
and determining the weather condition of the target area in the target time period according to the relative spiral degree of the storm.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
acquiring target environment wind data of a target area in a target time period, wherein the target time period comprises a first time period and a second time period which are adjacent in time sequence, the target environment wind data comprises environment wind data of the first time period and environment wind data of the second time period, the environment wind data of the first time period is obtained according to radar echo data measured by a Doppler weather radar at the starting moment of the first time period, the environment wind data of the second time period is obtained through calculation of a numerical weather forecast model, and the environment wind data comprises radial wind speed and latitudinal wind speed;
calculating the relative wind storm helicity according to the target environment wind data, wherein the relative wind storm helicity is used for indicating the atmospheric motion intensity;
and determining the weather condition of the target area in the target time period according to the relative spiral degree of the storm.
The beneficial effects brought by the technical scheme provided by the embodiment of the application at least comprise:
the weather forecasting method, the weather forecasting device, the computer equipment and the storage medium can accurately forecast the strong convection weather. According to the weather forecasting method, firstly, environmental wind data of a first time period is obtained according to radar echo data measured by a Doppler weather radar at the starting moment of the first time period, then, environmental wind data of a second time period after the first time period is calculated according to a numerical weather forecasting model, target environmental wind data are determined according to the environmental wind data of the first time period and the environmental wind data of the second time period, storm relative helicity is calculated according to the target environmental wind data, the storm relative helicity is used for indicating storm change intensity, and weather conditions of a target area in the target time period are determined according to the storm relative helicity. In the embodiment of the application, the radar echo data measured by the Doppler weather radar is used for extrapolating to obtain the environmental wind data in the first time period, and then the environmental wind data in the second time period is calculated through the numerical weather forecasting model, so that the accuracy of the target environmental wind data in the target time period is ensured, the relative vorticity of a storm calculated according to the target environmental wind data is improved, and whether strong convection weather conditions possibly occur in the target time period in a target area can be accurately forecasted.
Drawings
Fig. 1 is a schematic diagram of an implementation environment of a weather forecasting method according to an embodiment of the present disclosure;
fig. 2 is a flowchart of a weather forecasting method according to an embodiment of the present disclosure;
FIG. 3 is a flow chart of a method for determining weather conditions according to an embodiment of the present disclosure;
FIG. 4 is a flow chart of another weather forecasting method provided in the embodiments of the present application;
FIG. 5 is a flow chart of a method for calculating the relative vorticity of a storm according to an embodiment of the present disclosure;
FIG. 6 is a schematic view of a storm curve according to an embodiment of the present application;
FIG. 7 is a flow chart of another weather forecasting method provided in the embodiments of the present application;
FIG. 8 is a flow chart of a method of calculating the relative vorticity of a storm according to an embodiment of the present disclosure;
FIG. 9 is a block diagram of a weather forecasting apparatus according to an embodiment of the present disclosure;
fig. 10 is a block diagram of a computer device according to an embodiment of the present application.
Detailed Description
To make the objects, technical solutions and advantages of the present application more clear, embodiments of the present application will be described in further detail below with reference to the accompanying drawings.
The weather forecast refers to the prediction of the state of the earth atmosphere at a certain place in the future by using modern scientific technology. The weather forecast can help people to know the future weather conditions in advance, so that production and life can be adjusted in advance according to the future weather conditions to avoid unnecessary loss.
In nature, the earth's atmosphere may have various different meteorological phenomena, wherein, strong convection weather is a special meteorological phenomenon, and the strong convection weather refers to a disastrous weather with phenomena of short-term strong precipitation, thunderstorm strong wind, tornado, hail, squall lines and the like. Strong convection weather often causes economic loss and even casualties. Since the duration of the strong convection weather is generally short and has obvious burstiness, it is necessary to provide a weather forecasting method capable of accurately forecasting the strong convection weather.
At present, with the wide application of Doppler weather radar, a meteorologist carries out multi-aspect research on the characteristics of radar echo data in the process of strong convection weather, in the prior art, short-time forecast of the strong convection weather mainly depends on the radar echo data measured by the Doppler weather radar, a current radar echo diagram sequence is obtained through analyzing the radar echo data, a future radar echo diagram sequence is generated based on the current radar echo diagram sequence, the future radar echo sequence is input into a pre-trained strong convection weather prediction model, and a strong convection weather prediction diagram is obtained. The strong convection weather prediction graph is used for indicating whether strong convection weather occurs in the future.
However, such forecast results often fall off rapidly in accuracy after 1 hour, and the trend of enhancement or reduction of strong convection weather cannot be predicted well.
The embodiment of the application provides a weather forecasting method, which is characterized in that radar echo data measured by a Doppler weather radar is extrapolated to obtain environmental wind data in a first time period, then the environmental wind data in a second time period is calculated through a numerical weather forecasting model, so that the accuracy of target environmental wind data in a target time period is ensured, the relative vorticity of a storm calculated according to the target environmental wind data is improved, and whether strong convection weather conditions possibly occur in a target time period in a target area can be accurately forecasted.
In the following, a brief description will be given of an implementation environment related to the weather forecasting method provided in the embodiment of the present application.
Fig. 1 is a schematic diagram of an implementation environment related to a weather forecasting method provided in the embodiment of the present application, and as shown in fig. 1, the implementation environment may include a server 101, a numerical weather forecasting model 102, and a doppler weather radar system 103, where the server 101 communicates with the numerical weather forecasting model 102 and the doppler weather radar system 103 through a wired network or a wireless network, respectively.
The server 101 may be a single server or a server cluster including a plurality of servers.
In the implementation environment shown in fig. 1, the doppler weather radar system 103 may send the ambient wind data of the first time period to the server 101, the numerical weather forecast model 102 may send the ambient wind data of the second time period to the server 101, and the server 101 may obtain the target ambient wind data in the target time period according to the ambient wind data of the first time period and the ambient wind data of the second time period, then calculate the relative helicity of the storm according to the target ambient wind data, and determine the weather condition of the target area in the target time period according to the relative helicity of the storm.
Referring to fig. 2, a flowchart of a weather forecasting method provided by an embodiment of the present application is shown, where the weather forecasting method may be applied in a server in the implementation environment shown in fig. 1, and as shown in fig. 2, the weather forecasting method may include the following steps:
in step 201, a server acquires target environmental wind data of a target area in a target time period.
In the embodiment of the present application, the starting time of the first time period is set to be time T.
The target time period comprises a first time period and a second time period which are adjacent in time sequence, and the sudden and temporary characteristics of strong convection weather are obvious, so that the forecast of the strong convection weather is a temporary forecast, the forecast duration of the temporary forecast is generally short, and the optional temporary forecast duration can be a duration of two to three hours in the future.
The target ambient wind data includes ambient wind data for a first time period and ambient wind data for a second time period.
And obtaining the environmental wind data of the first time period according to radar echo data measured by the Doppler weather radar at the starting moment of the first time period.
And calculating the environmental wind data of the second time period by using a numerical weather forecast model, wherein the environmental wind data comprises radial wind speed and latitudinal wind speed.
In one embodiment of the present application, the process of the server obtaining the ambient wind data of the first time period may be: at the time T, the Doppler weather radar system carries out radar monitoring on the cloud layer of the target area to obtain radar echo data, the radar echo data are extrapolated by adopting an optical flow method, environmental wind data in a future period of time after the time T can be obtained, and the Doppler weather radar system can send the obtained environmental wind data in a future time point after the time T to the server. The corresponding duration from the moment T to a certain future time point is longer than the corresponding duration of the first time period.
The accuracy of environmental wind data obtained by extrapolation of radar echo data measured at the time T by a Doppler weather radar system is high within 1 hour, and the accuracy is reduced sharply after 1 hour. In order to ensure the accuracy of the environmental wind data, in the embodiment of the present application, the server may extract the environmental wind data of the first time period with the T time as a starting point from the environmental wind data in the target time period after the T time. Wherein the first time period is a time period within 1 hour with time T as a starting point.
In an embodiment of the present application, the process of the server acquiring the ambient wind data of the second time period may be: and acquiring meteorological data at the time T, wherein the meteorological data comprises wind field data, temperature field data, atmospheric humidity data, atmospheric pressure field data and the like. The weather data is input into a numerical weather forecast model, which can output weather forecast data from time T to a future time point, the weather forecast data including air pressure data, potential altitude data, temperature data, environmental wind data, and the like.
The model state of the numerical weather forecasting model is unstable when the numerical weather forecasting model starts to run, so that data output by the numerical weather forecasting model from the T moment to within half an hour is relatively chaotic and has no use value, and the accuracy of weather forecasting data output after 1 hour from the T moment is relatively high. Therefore, in the embodiment of the present application, the server may extract, from the weather forecast data output by the numerical weather forecast model from the time T to a future time point, the ambient wind data in the weather forecast data in the second time period 1 hour after the time T, that is, the ambient wind data in the second time period.
In the embodiment of the present application, the second time period is continuous with the first time period, the second time period takes an end point of the first time period as a starting point, and the duration of the second time period is generally 2 hours or 3 hours.
The relative vorticity of the storm is used for indicating the rotation degree of an environmental wind field in a certain air layer thickness and the vorticity of the environment in the fluid, and can be used for indicating the atmospheric motion strength. In the embodiment of the present application, a calculation formula of the relative helicity of the storm may be as shown in formula (1):
wherein SRH is storm relative helicity, and V represents environmental wind dataC represents the storm moving speed, h represents the air layer thickness, omegahRepresenting the horizontal vorticity vector.
The air layer thickness and the horizontal vorticity vector are known quantities, and the storm moving speed C can be calculated according to the environmental wind data. Therefore, the server can input the target environment wind data into the formula (1) to obtain the relative wind speed of the storm.
And step 203, the server determines the weather condition of the target area in the target time period according to the relative spiral degree of the storm.
As shown in fig. 3, the process of the server determining the weather conditions according to the relative helicity of the storm may include the following:
In the embodiment of the present application, the storm relative helicity interval may include, for example, the following first interval: less than 30; a second interval: greater than or equal to 30 and less than 80; the third interval: 80 or more and 150 or less; a fourth interval: greater than or equal to 150. Different storm relative helicity intervals correspond to different weather conditions.
Wherein, the weather condition corresponding to the first interval is: no precipitation. The weather conditions corresponding to the second interval are: there is weak precipitation. The weather conditions corresponding to the third section are: there is strong precipitation. The weather conditions corresponding to the fourth interval are: the super monomer storm and hail heavy wind severe weather conditions exist.
And 302, determining the weather condition corresponding to the relative spiral degree of the storm according to the relative spiral degree interval of the storm in which the relative spiral degree of the storm is located.
In the embodiment of the present application, for example, the relative vorticity of the storm is 120, and it can be known through comparison that the relative vorticity interval of the storm is the third interval, and the weather condition corresponding to the third interval is: there is strong precipitation.
And step 303, determining the weather condition of the target area in the target time period according to the weather condition corresponding to the relative helicity of the storm.
In the embodiment of the application, the weather condition corresponding to the relative spirality of the storm can be used as the weather condition of the target area in the target time period.
According to the weather forecasting method provided by the embodiment of the application, the radar echo data measured by the Doppler weather radar is extrapolated to obtain the environmental wind data in the first time period, and then the environmental wind data in the second time period is calculated through the numerical weather forecasting model, so that the accuracy of the target environmental wind data in the target time period is ensured, the relative vorticity of storm calculated according to the target environmental wind data is improved, and whether strong convection weather conditions possibly occur in the target time period in the target area can be accurately forecasted.
In the embodiment of the present application, as shown in fig. 4, the weather forecasting method may further include the following steps:
In the embodiment of the present application, the first time period may be divided into a plurality of first unit time periods, and optionally, the duration of each first unit time period may be 5 minutes or 10 minutes.
The server acquiring the ambient wind data in the first time period may refer to: the server acquires environmental wind data of each first unit time period in a first time period, and the environmental wind data in the first time period is multiple.
In the embodiment of the application, when the doppler weather radar system extrapolates according to the radar echo data, the environmental wind data of each first unit time period in the first time period can be directly extrapolated.
In this embodiment, the second time period may be divided into a plurality of second unit time periods, so that the doppler weather radar system and the environmental wind data output by the numerical weather forecast model can be well used, in this embodiment, the second unit time period is the same as the first unit time period, and optionally, the time length of each second unit time period may be 5 minutes or 10 minutes.
The server acquiring the environmental wind data in the second time period may refer to: the server acquires the environmental wind data of each second unit time period in the second time period, wherein the environmental wind data in the second time period are multiple.
In the embodiment of the present application, the numerical weather forecast model may directly output the environmental wind data of a plurality of second unit time periods in a time period from the time T to a future time point. The server may extract a plurality of second unit periods of ambient wind data within the second period of time from the plurality of second periods of ambient wind data.
In the embodiment of the present application, the server combines the environmental wind data of each first unit time period of the first time period and the environmental wind data of each second unit time period of the second time period according to the contents disclosed in step 401 and step 402 to obtain the target environmental wind data of the target time period.
By combining the plurality of environmental wind data of the first time period with the plurality of environmental wind data of the second time period, the relative helicity of the storm is calculated together, and the forecasting accuracy can be improved.
And step 403, calculating the relative wind speed of the storm according to the environmental wind data for each environmental wind data in the first time period and the second time period.
In the embodiment of the application, a first unit time period in a first time period and a second unit time period in a second time period correspond to the environmental wind data respectively. The server calculates the relative helicity of the storm according to the environmental wind data, and the method comprises the following steps: the server calculates the storm relative helicity of each first unit time period according to the environmental wind data of each first unit time period in the first time period. And the server calculates the storm relative helicity of each second unit time period according to the environmental wind data of each second unit time period in the second time period.
As shown in fig. 5, the process of the server calculating the storm relative helicity of each first unit time period according to the ambient wind data of each first unit time period in the first time period may include the steps of:
in step 501, the server calculates the storm movement speed according to the environmental wind data.
The storm movement speed includes a radial storm movement speed and a latitudinal storm movement speed.
In the embodiment of the application, for each first unit time period in the first time period, the storm relative helicity of the first unit time period is calculated according to the environmental wind data of the first unit time period.
In the embodiment of the application, calculating the storm moving speed according to the environmental wind comprises calculating the radial storm moving speed according to the radial wind speed and calculating the latitudinal storm moving speed according to the latitudinal wind speed.
In the embodiment of the present application, a radial wind coefficient and a latitudinal wind coefficient may be obtained, and the radial wind coefficient may be 0.75 or 1. The latitudinal wind coefficient may be 0.75 or 1. The server may multiply the radial wind coefficient by the radial wind speed to obtain the radial storm movement speed. The server can multiply the weftwise wind coefficient and the weftwise wind speed to obtain the moving speed of the weftwise storm.
In the embodiment of the present application, reference may be made to the content disclosed in step 202 for a process of calculating the relative spirality of the storm according to the environmental wind data and the storm moving speed, and details are not described herein again.
For each first unit time period within the first time period, the server may calculate a storm relative helicity for the first unit time period from the ambient wind data for the first unit time period and the storm movement speed for the first unit time period. Thus, a plurality of storm relative helicities over a first time period may be obtained.
The process of calculating the storm relative helicity of each second unit time period by the server according to the environmental wind data of each second unit time period in the second time period is the same as the content disclosed in steps 501 to 502, and is not described herein again. It can be seen that a plurality of storm relative helicities can also be obtained in the second time period.
And step 404, determining the weather condition of the target area in the target time period according to the relative spiral degree of the storm.
In this embodiment of the application, reference may be made to the content disclosed in step 203 for the process of determining the weather condition by the server according to the relative spirality of each storm, which is not described herein again.
In this embodiment, the server may determine the weather condition of each first unit time period according to the storm relative helicity of each first unit time period within the first time period. The server may determine the weather condition of each second unit time period from the storm relative helicity of each second unit time period within the second time period.
In the embodiment of the present application, for example, the first time period includes 12 first unit time periods, and accordingly, the 12 storm relative helicities and the weather conditions corresponding to the respective storm relative helicities can be obtained. For example, the second time period includes 24 second unit time periods, and accordingly, 24 storm relative helicities and weather conditions corresponding to the storm relative helicities can be obtained.
In the embodiment of the present application, the weather conditions of 36 unit time periods in the target time period can be obtained through 12 weather conditions in the first time period and 24 weather conditions in the second time period, so as to determine the weather conditions of the target area in the target time period, for example, as shown in table 1, as can be seen from table 1, the weather conditions of the target area in the target time period are changed from weak precipitation to strong precipitation.
TABLE 1
| First unit |
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 |
| |
30 | 30 | 50 | 50 | 50 | 50 | 60 | 60 | 60 | 60 | 75 | 75 |
| Weather conditions | Weak rainfall | Weak rainfall | Weak rainfall | Weak rainfall | Weak rainfall | Weak rainfall | Weak rainfall | Weak rainfall | Weak rainfall | Weak rainfall | Weak rainfall | Weak rainfall |
| Second unit |
13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 |
| |
80 | 80 | 90 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 |
| Weather conditions | Heavy precipitation | Heavy precipitation | Heavy precipitation | Heavy precipitation | Heavy precipitation | Heavy precipitation | Heavy precipitation | Heavy precipitation | Heavy precipitation | Heavy precipitation | Heavy precipitation | Heavy precipitation |
| Second unit |
25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 35 | 36 |
| SRH | 130 | 130 | 130 | 130 | 130 | 130 | 130 | 140 | 140 | 140 | 140 | 140 |
| Weather conditions | Heavy precipitation | Heavy precipitation | Heavy precipitation | Heavy precipitation | Heavy precipitation | Heavy precipitation | Heavy precipitation | Heavy precipitation | Heavy precipitation | Heavy precipitation | Heavy precipitation | Heavy precipitation |
In one embodiment of the present application, the relative spirality of the storm is multiple, and the weather forecasting method may further include the following: and generating a storm change curve according to the relative helicity of each storm. The storm change curve is used for indicating the storm change trend of the target area in the target time period.
In the embodiment of the present application, a schematic diagram of a storm change curve as shown in fig. 6 can be obtained by combining table 1, in fig. 6, a horizontal axis represents a first unit time period number and a second unit time period number, and a vertical axis represents a relative storm spirality. The greater the relative helicity of the storm, the stronger the rain.
According to the embodiment of the application, the plurality of first unit time periods are arranged in the first time period, the plurality of second unit time periods are arranged in the second time period, and the weather condition in the target time period is calculated according to the storm relative helicity SRH of each first unit time period or each second unit time period, so that the change trend of the convection weather can be predicted, and the accuracy of forecasting the strong convection weather is improved.
In an embodiment of the present application, the ambient wind data includes ambient wind data for each of a plurality of levels of atmosphere of the target area. As shown in fig. 7, the weather forecasting method may further include the steps of:
in step 701, a server acquires a plurality of environmental wind data of a first time period.
In the embodiment of the application, the server acquires the environmental wind data of each of the plurality of levels in the atmosphere of the target area in each first unit time period of the first time period.
The air flow of the convection weather mainly comes from the bottom layer, and in the embodiment of the application, the plurality of layers are ground layer, 925hPa aerostatic layer, 850hPa aerostatic layer, 700hPa aerostatic layer, 500hPa aerostatic layer and 400hPa aerostatic layer. In the embodiment of the present application, the environmental wind data of each layer mainly refers to ground layer environmental wind data, 925hPa atmospheric pressure layer environmental wind data, 850hPa atmospheric pressure layer environmental wind data, 700hPa atmospheric pressure layer environmental wind data, 500hPa atmospheric pressure layer environmental wind data, and 400hPa atmospheric pressure layer environmental wind data.
In the embodiment of the application, for each first unit time period, when the doppler weather radar system extrapolates according to the radar echo data, the environmental wind data of each of the plurality of levels of the atmosphere of the first unit time period can be extrapolated.
In step 702, the server obtains a plurality of environmental wind data for a second time period.
In the embodiment of the application, the server acquires the environmental wind data of each of the plurality of levels in the atmosphere of the target area in each second unit time period of the second time period.
For each second unit time period, the numerical weather prediction model may output ambient wind data for each of a plurality of levels of atmosphere for the second unit time period.
In step 703, the server obtains the storm relative helicity in the first time period according to the multiple environmental wind data in the first time period.
In this embodiment of the application, the server obtaining the storm relative helicity in the first time period includes: for each first unit time period of the first time period, the storm relative helicity of the first unit time period is calculated.
In this embodiment of the application, as shown in fig. 8, the process of calculating the storm relative helicity of each first unit time period by the server may include the following steps:
Wherein the storm movement speed comprises a radial storm movement speed and a latitudinal storm movement speed.
The average radial wind speed is calculated according to the radial wind speeds of the multiple layers, and a radial wind coefficient is obtained, and the server may multiply the average radial wind speed by the radial wind coefficient to obtain the radial storm moving speed (refer to the disclosure in step 501). The storm speed of movement is taken as the radial storm speed of movement for each level.
And calculating the average latitudinal wind speed according to the latitudinal wind speeds of the multiple layers to obtain a latitudinal wind coefficient, and multiplying the average latitudinal wind speed by the latitudinal wind coefficient by the server to obtain the latitudinal storm moving speed. The moving speed of the latitudinal storm is used as the moving speed of the latitudinal storm of each layer.
In one embodiment of the application, the mean radial wind speed may be the average of the radial wind speeds of 850hPa aerostatic layers to 400hPa aerostatic layers. The average weftwind speed may be the average of the weftwind speeds of 850hPa to 400hPa pneumatic layers.
It should be noted that, in the embodiment of the present application, the server may obtain an average wind direction, and the wind direction of the storm is 30 ° or 40 ° deflected to the right.
And step 802, for each layer in the atmosphere of the target area, calculating the relative spiral degree of the layer storm of the layer according to the environmental wind data of the layer and the storm moving speed of the layer.
The relative helicity of the layer storm can be represented by equation (2):
SRH'＝(Uk+1-Cx)(Vk-Cy)-(Uk-Cx)(Vk+1-Cy) (2)
wherein, Uk+1Indicates the weftwise wind speed, U, of the (k + 1) th layerkIndicating the weftwise wind speed, V, of the k-th levelk+1Represents the radial wind speed, V, of the k +1 th levelkRepresenting the radial wind speed, C, of the k-th levelxIndicating the speed of movement of a wind storm in the weft direction, CyRepresenting the radial storm speed of movement. k represents the hierarchy number of each level from bottom to top. k 1,2, N-1, N. N is the total number of levels, for example N may be 6.
And step 803, calculating the relative storm helicity of each layer in the atmosphere of the target area according to the relative storm helicity of the layer.
In the embodiment of the present application, the calculation of the storm relative helicity can be represented by formula (3):
in step 704, the server obtains the storm relative helicity in the second time period according to the plurality of environmental wind data in the second time period.
In this embodiment of the application, the server obtaining the storm relative helicity in the second time period includes: for each second unit time period of the second time period, the storm relative helicity of the second unit time period is calculated.
In the embodiment of the present application, the process of calculating the storm relative helicity of each second unit time period is the same as that disclosed in step 703, and details are not described here.
Reference may be made to the disclosure of step 404, which is not repeated herein.
According to the method and the device, the storm relative helicity of the first unit time period or the second unit time period is calculated according to the environmental wind data of each layer of the multiple layers of the atmosphere of the target area, so that the accuracy of the storm relative helicity is improved, and the accuracy of forecasting the strong convection weather is improved.
Referring to fig. 9, a block diagram of a weather forecasting apparatus provided in an embodiment of the present application is shown, where the weather forecasting apparatus may be configured in a server in the implementation environment shown in fig. 1. As shown in fig. 9, the weather forecast apparatus may include an acquisition module 901, a calculation module 902, and a determination module 903, wherein:
an obtaining module 901, configured to obtain target environment wind data of a target area in a target time period, where the target time period includes a first time period and a second time period which are adjacent in time sequence, the target environment wind data includes environment wind data of the first time period and environment wind data of the second time period, the environment wind data of the first time period is obtained according to radar echo data measured by a doppler weather radar at a start time of the first time period, the environment wind data of the second time period is obtained through calculation by a numerical weather forecast model, and the environment wind data includes a radial wind speed and a latitudinal wind speed;
the calculating module 902 is used for calculating the relative wind storm spirality according to the target environment wind data, and the relative wind storm spirality is used for indicating the atmospheric motion intensity;
and a determining module 903, configured to determine, according to the relative helicity of the storm, a weather condition of the target area in the target time period.
In an embodiment of the present application, the obtaining module 901 is further configured to obtain, in a plurality of first unit time periods in the first time period, environment wind data corresponding to each first unit time period through radar echo data measured by the doppler weather radar at the starting time of the first time period, so as to obtain a plurality of environment wind data in the first time period; and in a plurality of second unit time periods in the second time period, calculating and obtaining environmental wind data corresponding to each second unit time period through a numerical weather forecast model to obtain a plurality of environmental wind data in the second time period, wherein the time length of the first unit time period is the same as that of the second unit time period.
In an embodiment of the present application, the calculation module 902 is further configured to calculate, for each of the ambient wind data in the first time period and the second time period, a storm relative helicity from the ambient wind data.
In one embodiment of the present application, the calculation module 902 is further configured to calculate a storm movement speed according to the environmental wind data, where the storm movement speed includes a radial storm movement speed and a latitudinal storm movement speed; and calculating the relative wind storm spirality according to the environmental wind data and the wind storm moving speed.
In one embodiment of the present application, the ambient wind data includes ambient wind data for each of a plurality of levels of the atmosphere of the target area, and the calculating module 902 is further configured to calculate, for each level, a storm movement speed for the level based on the ambient wind data for the level; correspondingly, the storm relative helicity is calculated according to the environmental wind data, and the method comprises the following steps: calculating the relative helicity of the storm of each layer according to the environmental wind data of each layer and the storm moving speed of each layer; and calculating the relative spiral degree of the storm according to the relative spiral degree of the storm of each layer.
In an embodiment of the present application, there are a plurality of storm relative helicities, and the determining module 903 is further configured to generate a storm change curve according to each storm relative helicity, where the storm change curve is used to indicate a storm change trend of the target area in the target time period.
In an embodiment of the present application, the determining module 903 is further configured to obtain a plurality of storm relative helicity intervals, where different storm relative helicity intervals correspond to different weather conditions; determining the weather condition corresponding to the relative wind storm helicity according to the relative wind storm helicity interval in which the relative wind storm helicity is located; and determining the weather condition of the target area in the target time period according to the weather condition corresponding to the relative helicity of the storm.
For the specific definition of the weather forecasting device, reference may be made to the above definition of the weather forecasting method, which is not described herein again. The modules in the weather forecast apparatus may be implemented in whole or in part by software, hardware, and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment of the present application, a computer device is provided, and the computer device may be a server, and its internal structure diagram may be as shown in fig. 10. The computer device includes a processor, a memory connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The computer program is executed by a processor to implement a weather forecasting method.
Those skilled in the art will appreciate that the architecture shown in fig. 10 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment of the present application, there is provided a computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
acquiring target environment wind data of a target area in a target time period, wherein the target time period comprises a first time period and a second time period which are adjacent in time sequence, the target environment wind data comprises environment wind data of the first time period and environment wind data of the second time period, the environment wind data of the first time period is obtained according to radar echo data measured by a Doppler weather radar at the starting moment of the first time period, the environment wind data of the second time period is obtained through calculation of a numerical weather forecast model, and the environment wind data comprises radial wind speed and latitudinal wind speed; calculating the relative wind storm helicity according to the target environment wind data, wherein the relative wind storm helicity is used for indicating the atmospheric motion intensity; and determining the weather condition of the target area in the target time period according to the relative spiral degree of the storm.
In one embodiment of the application, the processor when executing the computer program further performs the steps of: in a plurality of first unit time periods in the first time period, obtaining environment wind data corresponding to each first unit time period through radar echo data measured by a Doppler weather radar at the starting moment of the first time period to obtain a plurality of environment wind data in the first time period; and in a plurality of second unit time periods in the second time period, calculating and obtaining environmental wind data corresponding to each second unit time period through a numerical weather forecast model to obtain a plurality of environmental wind data in the second time period, wherein the time length of the first unit time period is the same as that of the second unit time period.
In one embodiment of the application, the processor when executing the computer program further performs the steps of: for each ambient wind data in the first time period and the second time period, a storm relative helicity is calculated from the ambient wind data.
In one embodiment of the application, the processor when executing the computer program further performs the steps of: calculating storm movement speed according to the environmental wind data, wherein the storm movement speed comprises radial storm movement speed and latitudinal storm movement speed; and calculating the relative wind storm spirality according to the environmental wind data and the wind storm moving speed.
In one embodiment of the application, the ambient wind data comprises ambient wind data for each of a plurality of levels of the atmosphere of the target region, the processor when executing the computer program further performs the steps of: for each layer, calculating the storm moving speed of the layer according to the environmental wind data of the layer; correspondingly, the following steps can also be realized: calculating the relative helicity of the storm of each layer according to the environmental wind data of each layer and the storm moving speed of each layer; and calculating the relative spiral degree of the storm according to the relative spiral degree of the storm of each layer.
In one embodiment of the application, the storm relative helicity is plural, and the processor when executing the computer program further performs the steps of: and generating a storm change curve according to the relative helicity of each storm, wherein the storm change curve is used for indicating the storm change trend of the target area in the target time period.
In one embodiment of the application, the processor when executing the computer program further performs the steps of: acquiring a plurality of storm relative helicity intervals, wherein different storm relative helicity intervals correspond to different weather conditions; determining the weather condition corresponding to the relative wind storm helicity according to the relative wind storm helicity interval in which the relative wind storm helicity is located; and determining the weather condition of the target area in the target time period according to the weather condition corresponding to the relative helicity of the storm.
The implementation principle and technical effect of the computer device provided by the embodiment of the present application are similar to those of the method embodiment described above, and are not described herein again.
In an embodiment of the application, a computer-readable storage medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, carries out the steps of:
acquiring target environment wind data of a target area in a target time period, wherein the target time period comprises a first time period and a second time period which are adjacent in time sequence, the target environment wind data comprises environment wind data of the first time period and environment wind data of the second time period, the environment wind data of the first time period is obtained according to radar echo data measured by a Doppler weather radar at the starting moment of the first time period, the environment wind data of the second time period is obtained through calculation of a numerical weather forecast model, and the environment wind data comprises radial wind speed and latitudinal wind speed; calculating the relative wind storm helicity according to the target environment wind data, wherein the relative wind storm helicity is used for indicating the atmospheric motion intensity; and determining the weather condition of the target area in the target time period according to the relative spiral degree of the storm.
In one embodiment of the application, the computer program, when executed by the processor, may further implement the steps of: in a plurality of first unit time periods in the first time period, obtaining environment wind data corresponding to each first unit time period through radar echo data measured by a Doppler weather radar at the starting moment of the first time period to obtain a plurality of environment wind data in the first time period; and in a plurality of second unit time periods in the second time period, calculating and obtaining environmental wind data corresponding to each second unit time period through a numerical weather forecast model to obtain a plurality of environmental wind data in the second time period, wherein the time length of the first unit time period is the same as that of the second unit time period.
In one embodiment of the application, the computer program, when executed by the processor, may further implement the steps of: for each ambient wind data in the first time period and the second time period, a storm relative helicity is calculated from the ambient wind data.
In one embodiment of the application, the computer program, when executed by the processor, may further implement the steps of: calculating storm movement speed according to the environmental wind data, wherein the storm movement speed comprises radial storm movement speed and latitudinal storm movement speed; and calculating the relative wind storm spirality according to the environmental wind data and the wind storm moving speed.
In one embodiment of the application, the ambient wind data comprises ambient wind data for each of a plurality of levels of the atmosphere of the target region, and the computer program, when executed by the processor, is further operable to perform the steps of: for each layer, calculating the storm moving speed of the layer according to the environmental wind data of the layer; correspondingly, the following steps can also be realized: calculating the relative helicity of the storm of each layer according to the environmental wind data of each layer and the storm moving speed of each layer; and calculating the relative spiral degree of the storm according to the relative spiral degree of the storm of each layer.
In an embodiment of the application, where there are a plurality of storm relative helicities, the computer program when executed by the processor may further perform the steps of: and generating a storm change curve according to the relative helicity of each storm, wherein the storm change curve is used for indicating the storm change trend of the target area in the target time period.
In one embodiment of the application, the computer program, when executed by the processor, may further implement the steps of: acquiring a plurality of storm relative helicity intervals, wherein different storm relative helicity intervals correspond to different weather conditions; determining the weather condition corresponding to the relative wind storm helicity according to the relative wind storm helicity interval in which the relative wind storm helicity is located; and determining the weather condition of the target area in the target time period according to the weather condition corresponding to the relative helicity of the storm.
The implementation principle and technical effect of the computer-readable storage medium provided in the embodiment of the present application are similar to those of the method embodiment described above, and are not described herein again.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the claims. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A weather forecasting method, the method comprising:
acquiring target environment wind data of a target area in a target time period, wherein the target time period comprises a first time period and a second time period which are adjacent in time sequence, the target environment wind data comprises environment wind data of the first time period and environment wind data of the second time period, the environment wind data of the first time period is obtained according to radar echo data measured by a Doppler weather radar at the starting moment of the first time period, the environment wind data of the second time period is obtained through calculation of a numerical weather forecast model, and the environment wind data comprises radial wind speed and latitudinal wind speed;
calculating storm relative helicity according to the target environment wind data, wherein the storm relative helicity is used for indicating the movement intensity of the atmosphere;
and determining the weather condition of the target area in the target time period according to the relative spiral degree of the storm.
2. The method of claim 1, wherein the obtaining target ambient wind data for a target area over a target time period comprises:
in a plurality of first unit time periods in the first time period, acquiring environmental wind data corresponding to each first unit time period through radar echo data measured by the Doppler weather radar at the starting moment of the first time period to obtain a plurality of environmental wind data in the first time period;
and in a plurality of second unit time periods in the second time period, calculating and obtaining environmental wind data corresponding to each second unit time period through the numerical weather forecast model to obtain a plurality of environmental wind data in the second time period, wherein the time length of the first unit time period is the same as that of the second unit time period.
3. The method of claim 2, wherein said calculating storm relative helicity from said target ambient wind data comprises:
for each of the ambient wind data over the first and second time periods, calculating the storm relative helicity from the ambient wind data.
4. The method of claim 3, wherein said calculating said storm relative helicity from said ambient wind data comprises:
calculating storm moving speed according to the environment wind data, wherein the storm moving speed comprises radial storm moving speed and latitudinal storm moving speed;
and calculating the relative spiral degree of the storm according to the environmental wind data and the storm moving speed.
5. The method of claim 4, wherein the ambient wind data comprises ambient wind data for each of a plurality of levels of the atmosphere of the target area, and wherein calculating the storm speed of movement from the ambient wind data comprises:
for each layer, calculating the storm moving speed of the layer according to the environmental wind data of the layer;
correspondingly, the calculating the relative storm helicity according to the environmental wind data includes:
calculating the relative helicity of the storm of each layer according to the environmental wind data of each layer and the storm moving speed of each layer;
and calculating the relative storm helicity according to the relative storm helicity of each layer.
6. The method of claim 1, wherein there are a plurality of said storm relative helicities, the method further comprising:
and generating a storm change curve according to each storm relative helicity, wherein the storm change curve is used for indicating the storm change trend of the target area in the target time period.
7. The method of claim 1, wherein said determining weather conditions of said target area over said target time period from said storm relative helicity comprises:
acquiring a plurality of storm relative helicity intervals, wherein different storm relative helicity intervals correspond to different weather conditions;
determining a weather condition corresponding to the storm relative helicity according to the storm relative helicity interval in which the storm relative helicity is located;
and determining the weather condition of the target area in the target time period according to the weather condition corresponding to the relative spirality of the storm.
8. A weather forecasting apparatus, characterized in that the apparatus comprises:
the system comprises an acquisition module, a processing module and a display module, wherein the acquisition module is used for acquiring target environment wind data of a target area in a target time period, the target time period comprises a first time period and a second time period which are adjacent in time sequence, the target environment wind data comprises environment wind data of the first time period and environment wind data of the second time period, the environment wind data of the first time period is obtained according to radar echo data measured by a Doppler weather radar at the starting moment of the first time period, the environment wind data of the second time period is obtained through calculation of a numerical weather forecast model, and the environment wind data comprises radial wind speed and latitudinal wind speed;
the calculating module is used for calculating storm relative helicity according to the target environment wind data, and the storm relative helicity is used for indicating the atmospheric motion intensity;
and the determining module is used for determining the weather condition of the target area in the target time period according to the relative spiral degree of the storm.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor, when executing the computer program, implements the steps of the method of any of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 7.
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